Flood Loss Models and Risk Analysis for Private Households in Can Tho City, Vietnam
Abstract
:1. Introduction
- -
- Among the available methods, which one provides the best result for developing flood loss models for residential buildings and contents in Can Tho city?
- -
- How can flood risk in data scarce conditions such as in Can Tho City be analyzed?
2. Case Study
2.1. Case Study
2.2. Data to Develop Loss Models
2.3. Data to Analyze Flood Risk
2.3.1. Flood Hazard Scenarios
2.3.2. Flood Duration Map
2.3.3. Building Map (Exposure)
3. Methods
3.1. Development of Flood Loss Models
- Depth–damage functions are developed by using linear and square root regression methods.Linear function (LR):Square root function (SRR):
- Four regression tree models are developed:Regression tree with one variable—water depth RT1Regression tree with two variables—water depth, duration RT2Regression tree with three variables—water depth, duration, floor space of building RT3:
3.2. Flood Risk Analysis
Expected Annual Damage (EADs)
4. Results and Discussion
4.1. Flood Loss Models
4.1.1. Depth-Damage Functions
4.1.2. Regression Trees with Only Water Depth as Predictor—RT1
4.1.3. Regression Trees with Water Depth and Duration as Predictors—RT2
4.1.4. Regression Trees with Water Depth, Duration and Floor Space of Building as Predictors—RT3
4.1.5. Regression Trees with Water Depth, Duration, Floor Space of Building and Building/Contents Value as Predictors—RT4
4.1.6. Comparison of Model Performance
4.2. Flood Risk Analysis
4.2.1. Risk Curves
4.2.2. Expected Annual Damage (EADs)
5. Conclusions
Acknowledgments
Author Contributions
Conflicts of Interest
References
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Groups | Order | Abbreviation | Predictors | Range in Data Set |
---|---|---|---|---|
Hydrologic, hydraulic aspects | 1 | wst | Water depth | 2 cm to 120 cm above ground |
2 | d | Inundation duration | 4 to 1040 h | |
Building/content characteristic | 3 | fsb | Floor space of building | 6 to 650 m2 |
4_1 | bv | Building value 1 | US$342 to 142,613 | |
4_2 | cv | Content value 1 | US$95 to 42,290 | |
Abbreviation | Response Variables | Range in Data Set | ||
Losses | A | Lossb | Building loss 1 | US$0 to 13,311 |
B | Lossc | Contents loss 1 | US$0 to 4754 |
Flood Hazard Maps | Annual Probability of Non-Exceedance | Mean Absolute Difference of Risk Estimation (%) | |||||
---|---|---|---|---|---|---|---|
Building | Content | ||||||
UHM 1 | ULM 2 | UHM-LM 3 | UHM | ULM | UHM-LM | ||
Fluvial hazard maps | 0.5 | 59 | 12 | 85 | 65 | 11 | 90 |
0.8 | 33 | 15 | 51 | 45 | 12 | 61 | |
0.9 | 39 | 12 | 59 | 39 | 11 | 59 | |
0.95 | 34 | 12 | 48 | 36 | 9 | 54 | |
0.98 | 28 | 11 | 45 | 30 | 11 | 48 | |
0.99 | 28 | 10 | 51 | 28 | 9 | 41 | |
Average | 44 | 14 | 68 | 49 | 12 | 71 | |
Pluvial hazard maps | 0.5 | 110 | 11 | 150 | 111 | 8 | 141 |
0.8 | 82 | 16 | 112 | 77 | 16 | 97 | |
0.9 | 56 | 18 | 84 | 58 | 13 | 74 | |
0.95 | 40 | 19 | 67 | 41 | 13 | 60 | |
0.98 | 25 | 19 | 53 | 23 | 13 | 40 | |
0.99 | 17 | 17 | 39 | 19 | 14 | 35 | |
Average | 66 | 20 | 101 | 66 | 15 | 89 | |
Combined fluvial–pluvial hazard maps | 0.5 | 70 | 13 | 97 | 66 | 13 | 86 |
0.8 | 40 | 15 | 62 | 38 | 10 | 60 | |
0.9 | 28 | 14 | 49 | 29 | 12 | 50 | |
0.95 | 23 | 14 | 39 | 26 | 8 | 40 | |
0.98 | 17 | 12 | 35 | 22 | 11 | 37 | |
0.99 | 20 | 11 | 33 | 21 | 11 | 35 | |
Average | 40 | 16 | 63 | 41 | 13 | 62 |
Models/Quantile Map | Building Loss (US$1000) | Content Loss (US$1000) | Total Loss (US$1000) | |||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
5% | 50% | 95% | MAD (%) | 5% | 50% | 95% | MAD (%) | 5% | 50% | 95% | MAD (%) | |
LR | 774 | 1522 | 2006 | 40 | 172 | 338 | 449 | 41 | 946 | 1860 | 2455 | 41 |
SRR | 749 | 1497 | 1985 | 41 | 162 | 326 | 438 | 42 | 911 | 1823 | 2423 | 41 |
RT1 | 556 | 1167 | 1564 | 43 | 134 | 264 | 370 | 45 | 689 | 1431 | 1935 | 44 |
RT2 | 916 | 1736 | 2228 | 38 | 215 | 404 | 532 | 39 | 1131 | 2140 | 2760 | 38 |
RT3 | 959 | 1859 | 2341 | 37 | 209 | 403 | 547 | 42 | 1168 | 2262 | 2889 | 38 |
Average | 791 | 1556 | 2025 | 40 | 178 | 347 | 467 | 42 | 969 | 1903 | 2492 | 40 |
MAD (%) | 26 | 23 | 19 | 59 * | 24 | 21 | 20 | 61 * | 25 | 22 | 19 | 59 * |
Models/Quantile Map | Building Loss (US$1000) | Content Loss (US$1000) | Total Loss (US$1000) | |||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
5% | 50% | 95% | MAD (%) | 5% | 50% | 95% | MAD (%) | 5% | 50% | 95% | MAD (%) | |
LR | 287 | 1112 | 1923 | 74 | 60 | 233 | 409 | 75 | 347 | 1345 | 2332 | 74 |
SRR | 265 | 1041 | 1862 | 77 | 51 | 203 | 379 | 81 | 316 | 1244 | 2241 | 77 |
RT1 | 200 | 809 | 1487 | 80 | 54 | 200 | 332 | 69 | 254 | 1010 | 1819 | 78 |
RT2 | 409 | 1481 | 2447 | 69 | 83 | 320 | 83 | 62 | 492 | 1801 | 2930 | 68 |
RT3 | 447 | 1706 | 2707 | 66 | 93 | 347 | 513 | 61 | 540 | 2053 | 3220 | 65 |
Average | 322 | 1230 | 2085 | 72 | 68 | 261 | 423 | 68 | 390 | 1490 | 2508 | 71 |
MAD (%) | 43 | 40 | 32 | 113 * | 35 | 32 | 57 | 114 * | 41 | 39 | 30 | 110 * |
Models/Quantile Map | Building Loss (US$1000) | Content Loss (US$1000) | Total Loss (US$1000) | |||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
5% | 50% | 95% | MAD (%) | 5% | 50% | 95% | MAD (%) | 5% | 50% | 95% | MAD (%) | |
LR | 1078 | 2596 | 3823 | 53 | 235 | 563 | 835 | 53 | 1314 | 3159 | 4659 | 53 |
SRR | 1031 | 2504 | 3747 | 54 | 217 | 523 | 796 | 55 | 1248 | 3027 | 4543 | 54 |
RT1 | 768 | 1949 | 2977 | 57 | 189 | 460 | 683 | 54 | 957 | 2409 | 3660 | 56 |
RT2 | 1339 | 3169 | 4550 | 51 | 304 | 707 | 982 | 48 | 1643 | 3876 | 5532 | 50 |
RT3 | 1429 | 3497 | 4898 | 50 | 306 | 733 | 1028 | 49 | 1735 | 4230 | 5926 | 50 |
Average | 1129 | 2743 | 3999 | 52 | 250 | 597 | 865 | 51 | 1379 | 3340 | 4864 | 52 |
MAD (%) | 31 | 30 | 25 | 80 * | 25 | 24 | 21 | 75 * | 30 | 29 | 24 | 79 * |
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Chinh, D.T.; Dung, N.V.; Gain, A.K.; Kreibich, H. Flood Loss Models and Risk Analysis for Private Households in Can Tho City, Vietnam. Water 2017, 9, 313. https://doi.org/10.3390/w9050313
Chinh DT, Dung NV, Gain AK, Kreibich H. Flood Loss Models and Risk Analysis for Private Households in Can Tho City, Vietnam. Water. 2017; 9(5):313. https://doi.org/10.3390/w9050313
Chicago/Turabian StyleChinh, Do Thi, Nguyen Viet Dung, Animesh K. Gain, and Heidi Kreibich. 2017. "Flood Loss Models and Risk Analysis for Private Households in Can Tho City, Vietnam" Water 9, no. 5: 313. https://doi.org/10.3390/w9050313